---
phase: 01-foundation
status: passed
score: 5/5
verified: 2026-02-20
---

# Phase 1: Foundation Verification Report

**Phase Goal:** Developers can import pcn_torch and instantiate a configured PCNLayer with chosen activation function
**Verified:** 2026-02-20T19:27:57Z
**Status:** passed
**Re-verification:** No -- initial verification

---

## Must-Have Verification

### Observable Truths

| # | Truth | Status | Evidence |
|---|-------|--------|----------|
| 1 | pip install -e . (via uv sync --dev) installs without errors | VERIFIED | .venv present, package importable, _version.py generated as 0.0.0.dev12+gc7a36e4b5 |
| 2 | from pcn_torch import PCNLayer succeeds and PCNLayer is nn.Module subclass | VERIFIED | issubclass(PCNLayer, nn.Module) confirmed in live Python session; test_is_nn_module_subclass passes |
| 3 | PCNLayer accepts configurable dims/activation, forward pass produces correct shapes | VERIFIED | PCNLayer(784,500,activation=relu).forward(randn(32,784)) returns (32,500),(32,500); weight shape (500,784) |
| 4 | Ruff, mypy, and pytest all pass (CI covers Python 3.10-3.13) | VERIFIED | ruff check: 0 errors; ruff format: 7 files formatted; mypy: 0 issues in 5 files; pytest: 32/32 passed |
| 5 | sigmoid, tanh, relu, identity available with hand-coded derivatives (no autograd) | VERIFIED | All 4 derivative functions confirmed; source inspection: no grad/backward usage |

**Score:** 5/5 truths verified

---

## Artifact Verification

| Artifact | Lines | Exists | Substantive | Wired | Status |
|----------|-------|--------|-------------|-------|--------|
| pyproject.toml | 71 | YES | hatchling+hatch-vcs, ruff/mypy/pytest config, dependency-groups.dev | build system entry point for uv sync | VERIFIED |
| src/pcn_torch/__init__.py | 19 | YES | re-exports PCNLayer, get_activation, __version__, type aliases; __all__ defined | imported by every consumer and test | VERIFIED |
| src/pcn_torch/_types.py | 12 | YES | ActivationFn, ActivationDeriv, ActivationPair TypeAlias definitions | imported via TYPE_CHECKING in activations.py; directly in __init__.py | VERIFIED |
| src/pcn_torch/activations.py | 72 | YES | 8 named functions + registry dict + get_activation() with ValueError handling | imported by layers.py and __init__.py; tested by test_activations.py | VERIFIED |
| src/pcn_torch/layers.py | 54 | YES | PCNLayer(nn.Module) with __init__, forward, extra_repr; Xavier init; no bias | imported by __init__.py; tested by test_layers.py | VERIFIED |
| .github/workflows/ci.yml | 46 | YES | 3 jobs (lint, typecheck, test); matrix 3.10/3.11/3.12/3.13; astral-sh/setup-uv@v7 with cache | wired to main push + PR triggers | VERIFIED |
| tests/test_activations.py | 112 | YES | 15 tests: registry lookup, ValueError, per-activation fn+deriv correctness with torch.allclose | 15/15 passing in pytest | VERIFIED |
| tests/test_layers.py | 101 | YES | 17 tests: subclass check, construction variants, forward shapes, parameter registration, no-bias | 17/17 passing in pytest | VERIFIED |
| src/pcn_torch/_version.py | auto | YES | auto-generated by hatch-vcs; version 0.0.0.dev12+gc7a36e4b5 | imported by __init__.py inside try/except | VERIFIED |

---

## Key Link Verification

| From | To | Via | Status | Evidence |
|------|----|-----|--------|----------|
| src/pcn_torch/layers.py | src/pcn_torch/activations.py | get_activation(activation) in PCNLayer.__init__ | WIRED | Line 8: import get_activation; line 31: act_fn, act_deriv = get_activation(activation) |
| src/pcn_torch/activations.py | src/pcn_torch/_types.py | TYPE_CHECKING guard for ActivationPair annotation | WIRED | Lines 10-11: if TYPE_CHECKING: from pcn_torch._types import ActivationPair; used in _ACTIVATIONS dict and get_activation return type |
| src/pcn_torch/__init__.py | src/pcn_torch/layers.py | from pcn_torch.layers import PCNLayer | WIRED | Line 5: direct import; PCNLayer in __all__ |
| src/pcn_torch/__init__.py | src/pcn_torch/activations.py | from pcn_torch.activations import get_activation | WIRED | Line 4: direct import; get_activation in __all__ |
| src/pcn_torch/__init__.py | src/pcn_torch/_types.py | from pcn_torch._types import ActivationDeriv, ActivationFn, ActivationPair | WIRED | Line 3: direct import; all three in __all__ |
| pyproject.toml | src/pcn_torch/_version.py | hatch-vcs version-file hook | WIRED | [tool.hatch.build.hooks.vcs] version-file = src/pcn_torch/_version.py; file confirmed generated |

---

## Requirements Coverage

| Requirement | Status | Evidence |
|-------------|--------|----------|
| PKG-01 -- Installable package (pip install -e . / uv sync --dev) | SATISFIED | Package installs via uv sync --dev; importable as pcn_torch; pyproject.toml uses hatchling build backend |
| PKG-05 -- CI pipeline (lint, typecheck, test across Python 3.10-3.13) | SATISFIED | .github/workflows/ci.yml has 3 jobs; test matrix covers 3.10/3.11/3.12/3.13; astral-sh/setup-uv@v7 |
| MOD-01 -- PCNLayer as nn.Module subclass with configurable in_features, out_features, activation | SATISFIED | PCNLayer(nn.Module) confirmed; keyword-only activation param; weight shape (out_features, in_features) |
| MOD-06 -- Hand-coded activation derivatives (no autograd) | SATISFIED | All 4 derivatives are pure tensor arithmetic; source inspection confirms zero autograd usage |

---

## Anti-Patterns Found

| File | Pattern | Severity | Notes |
|------|---------|----------|-------|
| None | -- | -- | No TODO/FIXME, no placeholder returns, no empty handlers found in any source file |

---

## Human Verification Required

The following item cannot be verified programmatically and warrants a one-time human check if desired:

### 1. CI Run on GitHub

**Test:** Push a commit to the main branch (or open a PR) and observe the Actions tab.
**Expected:** All three jobs (lint, typecheck, test with 4-way Python matrix) complete green.
**Why human:** The CI workflow file is structurally correct and all commands pass locally. The GitHub Actions execution environment (Ubuntu runners, PyPI access, uv cache, Python 3.10-3.13 matrix) can only be confirmed by actually triggering a run. This is environmental validation, not a gap.

---

## Verification Summary

All 5 success criteria are fully met. The phase goal is achieved.

- **Package installation:** uv sync --dev installs pcn-torch in editable mode with hatchling + hatch-vcs. _version.py is auto-generated (0.0.0.dev12+gc7a36e4b5). pyproject.toml is complete with all tool configs.
- **PCNLayer importability and inheritance:** from pcn_torch import PCNLayer works. PCNLayer is confirmed nn.Module subclass at both class and instance level.
- **Configurable construction and correct forward shapes:** PCNLayer(784,500,activation=relu) constructs with weight.shape==(500,784). forward(randn(32,784)) returns (prediction,preactivation) both shape (32,500). Batch sizes 1, 16, 32, 128 all tested and passing.
- **Quality gates:** ruff check 0 errors, ruff format 0 differences, mypy 0 issues across 5 source files, pytest 32/32 passed. CI workflow covers Python 3.10-3.13 with astral-sh/setup-uv@v7.
- **Hand-coded derivatives:** All 4 activations have named derivative functions using only torch tensor operations. No autograd, no .grad, no .backward(). ReLU derivative at zero is 0 (x > 0 convention). Tanh, sigmoid, identity derivatives verified with torch.allclose against manual formulas in test suite.

---

*Verified: 2026-02-20T19:27:57Z*
*Verifier: Claude (gsd-verifier)*
